Fluorescence microscopy

Acquiarium is for carrying out the common pipeline of many spatial cell studies using fluorescence microscopy. It addresses image capture, raw image correction, image segmentation, quantification of segmented objects and their spatial arrangement, volume rendering, and statistical evaluation. It is focused on quantification of spatial properties of many objects and their mutual spatial relations in a collection of many 3D images. It can be used for analysis of a collection of 2D images or time lapse series of 2D or 3D images as well. It has a modular design and is extensible via plug-ins. It is a stand-alone, easy to install application written in C++ language. The GUI is written using cross-platform wxWidgets library.

An ImageJ macro for correcting frame drift occurred during image acquisition.

It often happens that you have an image sequence that shows problematic drifting of image frame and at the same time you have some landmarks that could be used for correcting the drift. This ImageJ macro allows you to Manually track the landmark using ImageJ Manual Tracking Plugin. Using the coordinates recorded in the Result window, each frame is shifted back so that the landmark stays in a single place.

‘’’Squassh’’’ is a tool for 2D and 3D segmentation and quantification of subcellular shapes in fluorescence microscopy images. It provides globally optimal detection and segmentation of objects with constant internal intensity distribution, followed by object-based colocalization analysis. The segmentation computed by Region Competition can optionally correct for the PSF of the microscope, hence providing optimally deconvolved segmentations. Part of the mosaic suite

Image segmentation based on the MOSAIC Discrete region competition algorithm. 

Easy-to-use, computationally efficient, two- and three-dimensional, feature point-tracking tool for the automated detection and analysis of particle trajectories as recorded by video imaging in cell biology. 

The tracking process requires no apriori mathematical modelling of the motion, it is self-initialising, it discriminates spurious detections, and it can handle temporary occlusion as well as particle appearance and disappearance from the image region. 

The plugin is well suited for video imaging in cell biology relying on low-intensity fluorescence microscopy. It allows the user to visualize and analyze the detected particles and found trajectories in various ways:

• Preview and save detected particles for separate analysis
• Global non progressive view on all trajectories
• Focused progressive view on individually selected trajectory
• Focused progressive view on trajectories in an area of interest

It also allows the user to find trajectories from uploaded particles position and information text files and then to plot particles parameters vs. time - along a trajectory